Data quality and observability for enterprise buyers
Asked as “data observability platform”, and as “data quality tool”, on behalf of an enterprise B2B company. 51 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each. Added to the October 2026 Edition on October 4, 2026; its answers are read by the distilled judge (ai-indexes-judge-qwen3-14b-run3), not the claude-opus-5 judge of the earlier categories: how the two compare.
Standing · first-choice share
41%
Clear leader
41Monte Carlo10Acceldata08Informatica Data Quality41others
41% of first choices, clear leader.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment; they sit side by side and are never added together.
The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrant
Show the two products at 0%, ordered by negative rate
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
All fifteen head-to-head pages: the top six products, each against each
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
01
02
03
04
05
06
07
08
09
10
11
12Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative60%
Key
01Monte Carlo41%
Monte Carlo41%02Acceldata10%
Acceldata10%03Informatica Intelligent Data Management Cloud8%
Informatica Intelligent Data Management Cloud8%04Ataccama ONE4%
Ataccama ONE4%05Soda4%
Soda4%06Sifflet4%
Sifflet4%07Collibra Data Quality & Observability2%
Collibra Data Quality & Observability2%08Anomalo2%
Anomalo2%09Metaplane2%
Metaplane2%10Datadog2%
Datadog2%11Bigeye0%
Bigeye0%12Great Expectations0%
Great Expectations0%What they warned about
One of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, GPT-5.4 mini, Gemini 3.5 Flash, Perplexity Sonar, Grok 4.1 Fast, Mistral Small, DeepSeek V4 Flash, Qwen 3.7 Flash, Kimi K2, GLM 4.7 FlashX, MiniMax M2.5, GPT-6 Luna and Muse Glimmer 30B changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Datadog48%
10 of 21 labels negative · 8 of 14 models · 3 hard negative
“Platforms to Avoid for Your Use Case ... Per-GB ingestion + per-user seats = unpredictable at scale” Kimi K2, budget prompt
Monte Carlo19%
10 of 54 labels negative · 8 of 14 models
“Monte Carlo is often cited as a platform that requires sending production data to a vendor-operated service... may need to evaluate this carefully or avoid it” Mistral Small, negative prompt
Anomalo27%
7 of 26 labels negative · 6 of 14 models · 1 hard negative
“Avoid for **mission-critical** enterprise use until they demonstrate multi-year stability” DeepSeek V4 Flash, negative prompt
New Relic75%
6 of 8 labels negative · 5 of 14 models · 2 hard negative
“Platforms to Avoid for Your Use Case ... Usage-based + full platform user fees” Kimi K2, budget prompt
What they cite
Citations exist only for the models that return a source list: fourteen of the fourteen in this edition, and all six flagship models on the expanded tier.
Sites the answers cite
74 of 84 answers in this category came back with a source list, from 14 of 14 models: citations where the model returns them, or the search results it consulted. 1174 links across 261 sites, every framing counted. Ranked by the number of answers carrying the site or page. None of the 252 answers across every segment cited this index's own page for the category.
vendor site · Atlan37 answers · 46 citations · 12 models
vendor site · Acceldata33 answers · 58 citations · 13 models
27 answers · 29 citations · 13 models
vendor site · DQLabs25 answers · 33 citations · 11 models
vendor site · G222 answers · 36 citations · 11 models
vendor site · OpenObserve22 answers · 30 citations · 12 models
20 answers · 25 citations · 8 models
vendor site · Guideflow19 answers · 20 citations · 8 models
18 answers · 24 citations · 8 models
vendor site · G218 answers · 18 citations · 10 models
17 answers · 20 citations · 11 models
vendor site · Augment Code17 answers · 17 citations · 10 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
27 answers · 11 models
18 answers · 8 models
17 answers · 10 models
17 answers · 10 models
16 answers · 8 models
16 answers · 9 models
16 answers · 7 models
15 answers · 10 models
13 answers · 9 models
13 answers · 6 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best data observability platform”, “data observability platform”, “data quality and observability platforms”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| Monte Carlo montecarlo.ai | 41% | 148 | 135,000 | 23,412 | 24,468 | |||
| Acceldata acceldata.io | 10% | 53 | 880 | 23 | 60,654 | 3 | 5 | |
| Informatica Intelligent Data Management Cloud informatica.com | 8% | 259 | 390 | 1 | 73,321 | 120 | ||
| Informatica parent site Informatica Data Quality 8% | 8% | 14 | 14,800 | 1,414 | ||||
| Ataccama ONE ataccama.com | 4% | 103 | 90 | 0 | 2,552 | 14 | ||
| Soda soda.io | 4% | 97 | 165,000 | 348,802 | 1,651 | $401 | 9 | |
| Sifflet siffletdata.com | 4% | 22 | 320 | 4 | 921 | 1 | ||
| groundcover groundcover.com | 4% | 24 | 14,800 | 1,328 | 9,109 | $792 | 24 | |
| Collibra Data Quality & Observability collibra.com | 2% | 32 | 0 | 10,491 | $48 | 41 | 7 | |
| Anomalo anomalo.com | 2% | 68 | 880 | 9 | 788 | 3 |
Google's top ten for the three searches hold 19 sites; 4 of them are among the sites the models cited here (acceldata.io, datamation.com, dqlabs.ai, g2.com). The first result for “best data observability platform” is reddit.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best data observability platform for an enterprise B2B company?”Paraphrase“Which data quality tool would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade data quality and observability platforms and how do they differ?”Budget-constrained“What is the best data observability platform for a large company that needs predictable total cost across thousands of users?”Scale-constrained“We are a 5,000 person company with SSO, SOC 2 and procurement review requirements evaluating a data observability platform. What should we look at?”Negative“Which data quality and observability platforms should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5no first choiceInformatica Intelligent Data Management CloudChangedMonte CarloMonte Carlo, groundcoveragainst: Datadogno first choiceagainst: Anomalo, IBM, Monte Carlo
Four alternatives
Ataccama ONE, Bigeye, Collibra Data Quality & Observability, IBM InfoSphere QualityStageNine alternatives
Acceldata, Atlan, Bigeye, Collibra Data Quality & Observability, DQLabs, Great Expectations, Informatica Intelligent Data Management Cloud, OvalEdge, SodaTwo alternatives
Bigeye, New RelicGPT-5.4 miniMonte CarloInformatica Data QualityChangedBigeye, Monte CarloMetaplaneno first choicenothing named
Two alternatives
Bigeye, IBM watsonx.data integration / Databand lineage in IBM ecosystemTwo alternatives
Precisely Data Integrity Suite, SodaSix alternatives
Ataccama ONE, Atlan, Collibra Data Quality & Observability, Great Expectations, Informatica Intelligent Data Management Cloud, SodaOne alternative
SodaGemini 3.5 FlashMonte CarloInformatica Cloud Data Quality (CDQ) / IDMCChangedMonte CarloDQLabsagainst: New RelicAcceldataagainst: Acceldata, Anomalo, Databand, Datadog, Dynatrace, Great Expectations (GX) Core, IBM InfoSphere Information Analyzer, Informatica Intelligent Data Management Cloud, Monte Carlo, New Relic, Soda Core, Talend
Four alternatives
Acceldata, Anomalo, Sifflet, SodaThree alternatives
Anomalo, Ataccama ONE, Monte CarloFive alternatives
Acceldata, Anomalo, Collibra Data Quality & Observability, IBM Databand, SodaSix alternatives
Acceldata, Ataccama ONE, Grafana Cloud, OpenObserve, Soda, Soda CoreFour alternatives
Anomalo, Databand, Monte Carlo, SodaPerplexity SonarMonte CarloInformatica Intelligent Data Management CloudChangedAnomalo, Ataccama ONE, Informatica Intelligent Data Management Cloud, Monte CarloPrizmagainst: Datadog, Dynatraceno first choicenothing named
One alternative
BigeyeFour alternatives
Ataccama ONE, Collibra Data Quality & Observability, Monte Carlo, Talend Data QualityFive alternatives
Collibra Data Quality & Observability, Deequ, Great Expectations, SAP Data Quality / SAP Information Steward, TalendOne alternative
Monte CarloGrok 4.1 FastMonte Carloagainst: Datadog, Dynatrace, New Relic, SplunkInformatica Data QualityChangedInformatica Intelligent Data Management Cloud, Monte CarloMonte Carloagainst: Acceldata, Anomalo, Collibra Data Quality & Observability, Datadog, SodaAcceldata, Monte Carloagainst: Anomalo, Bigeye, Collibra Data Quality & Observability, Datadog, Grafana Cloud, Great Expectations, IBM InfoSphere, Informatica IDQ, Metaplane, Monte Carlo, Soda Core, SolarWinds, Talend
Three alternatives
Acceldata, Bigeye, MetaplaneFive alternatives
Ataccama ONE, Collibra Data Quality & Observability, IBM InfoSphere, Oracle EDQ, TalendEight alternatives
Acceldata, Anomalo, Ataccama ONE, Bigeye, DQLabs, Metaplane, SAS Data Quality, SiffletTwo alternatives
Bigeye, MetaplaneThree alternatives
Bigeye, Metaplane, SodaMistral SmallMonte Carlo, Siffletno first choiceChangedno first choicegroundcoveragainst: New RelicMonte Carloagainst: Deequagainst: Acceldata, Collibra Data Quality & Observability, Informatica Intelligent Data Management Cloud, Metaplane, Monte Carlo
One alternative
TelmaiFive alternatives
Azure Data Quality Services, Collibra Data Quality & Observability, Informatica Data Quality, Microsoft Purview, Talend Data QualityOne alternative
DatadogFive alternatives
Acceldata, Anomalo, Bigeye, Databand, SodaDeepSeek V4 FlashMonte Carloagainst: DatadogInformatica Data QualityChangedInformatica Intelligent Data Management Cloud, Monte CarloAcceldataagainst: Monte CarloMonte Carloagainst: Datafold, Metaplane, Sodaagainst: AWS CloudWatch, Anomalo, Azure Monitor, Bigeye, DQLabs, GCP Logging, Monte Carlo, Sifflet, Soda, Telmai
Two alternatives
Acceldata, BigeyeThree alternatives
Ataccama ONE, Collibra Data Quality & Observability, TalendEight alternatives
Acceldata, Anomalo, Ataccama ONE, Bigeye, Collibra Data Quality & Observability, DQLabs Prizm, Metaplane, SodaTwo alternatives
DQLabs, SiffletFour alternatives
Acceldata, Anomalo, Bigeye, SiffletLlama 4 Maverickno first choiceno first choiceHeldno first choiceCoralogixno first choicenothing named
Three alternatives
Augmentcode, Datadog, OpenObserveQwen 3.7 FlashMonte CarloInformatica Intelligent Data Management CloudChangedMonte Carloagainst: Informatica Intelligent Data Management CloudSodaagainst: Datadog, New Relicno first choicenothing named
Five alternatives
Acceldata, Atlan, Bigeye, Datafold, SnowsightTwo alternatives
Ataccama ONE, Collibra Data Quality & ObservabilityThree alternatives
Acceldata, Anomalo, SodaThree alternatives
Alation, Collibra Data Quality & Observability, Monte CarloKimi K2Acceldata, Monte CarloCollibra Data Quality & Observability, Monte CarloChangedBigeye, Monte CarloAcceldataagainst: Datadog, Dynatrace, Monte Carlo, New Relic, SplunkAnomalo, Monte Carloagainst: Anomalo, Bigeye, Monte Carlo
Three alternatives
Anomalo, Datadog, SiffletThree alternatives
Acceldata, Bigeye, Informatica Data QualityFour alternatives
Ataccama ONE, Collibra Data Quality & Observability, IBM Databand, Informatica Intelligent Data Management CloudOne alternative
BigeyeTwo alternatives
Bigeye, MetaplaneGLM 4.7 FlashXMonte CarloInformatica Intelligent Data Management CloudChangedBigeye, Monte CarloAtlan, Monte Carloagainst: Acceldata, IBM Databand, Sifflet, Unravel Datano first choiceagainst: Metaplane, Monte Carlo
Two alternatives
Bigeye, SiffletTwo alternatives
Ataccama ONE, Collibra Data Intelligence PlatformTen alternatives
Ataccama ONE, DataObservability, Datadog, Elementary, Great Expectations, IBM InfoSphere, Metaplane, Prizm, Sifflet, SodaFive alternatives
Bigeye, Datafold, Metaplane, OpenObserve, SodaMiniMax M2.5DatadogInformatica Data QualityChangedInformatica Intelligent Data Management Cloud, Monte CarloMonte Carlono first choicenothing named
Five alternatives
Chronosphere, Dynatrace, Grafana Labs, Sifflet, Splunk Observability CloudFour alternatives
AWS Glue DataBrew, Great Expectations, Microsoft Azure Data Factory, Talend Data QualityThree alternatives
Ataccama ONE, Collibra Data Quality & Observability, Great ExpectationsThree alternatives
Acceldata, Datafold, MetaplaneGPT-6 LunaMonte CarloAtaccama ONEChangedno first choiceSiffletno first choiceagainst: Soda, dbt
Three alternatives
Acceldata, Bigeye, SodaOne alternative
Informatica Cloud Data QualityTwo alternatives
Monte Carlo, ObserveMuse Glimmer 30BMonte CarloAtaccama ONEChangedAtaccama ONE, Monte CarloMonte Carlo, Sodano first choiceagainst: Anomalo, Bigeye, Datadog, Metaplane, Monte Carlo, Validio
Three alternatives
Bigeye, Datadog, SiffletThree alternatives
Collibra Data Quality, Informatica Data Quality, Informatica Intelligent Data Management CloudTwo alternatives
Bigeye, SodaTwo alternatives
Netdata, groundcoverBold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Eighty-four rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|---|---|---|---|---|---|
| Direct recommendation | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 23:07 | no | 0 | 4 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 01:25 | yes | 3 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 01:14 | yes | 12 | 25 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-04 23:57 | yes | 19 | 3 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 23:11 | yes | 24 | 9 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-05 00:34 | yes | 24 | 12 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 23:56 | yes | 24 | 40 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-05 01:11 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-05 01:27 | no | 0 | 24 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-05 01:13 | yes | 20 | 30 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 00:07 | yes | 21 | 26 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-05 00:03 | yes | 5 | 24 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-05 00:43 | yes | 4 | 16 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 23:52 | yes | 13 | 17 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 01:39 | yes | 9 | 9 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 01:30 | yes | 3 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:30 | yes | 9 | 24 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-05 01:39 | yes | 19 | 2 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-05 01:24 | yes | 23 | 8 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-05 00:00 | no | 0 | 2 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 22:59 | yes | 24 | 33 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-05 01:09 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-05 00:00 | yes | 10 | 39 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-05 00:20 | yes | 20 | 20 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 00:56 | yes | 15 | 17 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-05 00:59 | no | 0 | 33 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-04 23:38 | yes | 2 | 13 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-05 00:32 | yes | 14 | 17 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 00:16 | yes | 17 | 13 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 00:42 | yes | 7 | 7 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:16 | yes | 25 | 32 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-05 01:24 | yes | 16 | 7 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 23:50 | yes | 23 | 11 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-05 01:27 | yes | 15 | 8 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 01:54 | yes | 25 | 45 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 22:23 | yes | 5 | 3 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:38 | no | 0 | 28 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-05 00:06 | yes | 20 | 31 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 22:31 | yes | 15 | 68 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-05 01:16 | yes | 25 | 47 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-04 22:09 | yes | 10 | 43 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 23:22 | yes | 23 | 30 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 23:32 | yes | 17 | 9 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 01:05 | yes | 2 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:59 | yes | 22 | 34 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-05 01:04 | yes | 19 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 22:43 | yes | 20 | 11 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-05 00:05 | yes | 9 | 6 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 01:44 | yes | 24 | 47 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 22:10 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-05 01:05 | no | 0 | 33 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-05 00:30 | yes | 25 | 27 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 23:29 | yes | 24 | 74 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 23:36 | yes | 19 | 38 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-05 01:38 | yes | 3 | 28 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-05 01:16 | yes | 23 | 33 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 01:50 | yes | 27 | 20 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 01:19 | no | 0 | 13 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-04 22:36 | yes | 13 | 32 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-05 01:04 | yes | 18 | 6 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-05 00:15 | yes | 18 | 10 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 23:06 | no | 0 | 9 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 01:29 | yes | 22 | 48 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-05 00:29 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 23:32 | no | 0 | 28 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-05 01:35 | yes | 18 | 36 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 00:13 | yes | 23 | 25 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-05 00:03 | yes | 19 | 37 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-05 00:21 | yes | 3 | 29 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 23:29 | yes | 14 | 20 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 00:46 | yes | 17 | 9 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 23:15 | yes | 0 | 5 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:51 | yes | 23 | 27 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-05 00:26 | yes | 19 | 3 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-05 00:23 | yes | 23 | 14 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-05 00:20 | yes | 5 | 6 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 00:08 | yes | 23 | 77 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 23:41 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:28 | yes | 21 | 70 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 23:51 | yes | 23 | 27 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 22:50 | yes | 23 | 23 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 22:28 | yes | 22 | 36 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-05 00:26 | yes | 3 | 20 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 23:51 | yes | 22 | 30 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
Ataccama read as Ataccama ONE
Collibra read as Collibra Data Quality & Observability
Grafana read as Grafana Cloud
Informatica read as Informatica Intelligent Data Management Cloud
Informatica (IDMC/CLAIRE) read as Informatica Intelligent Data Management Cloud
Informatica (IDQ) read as Informatica Intelligent Data Management Cloud
Unresolved, counted raw
Augmentcode
Azure Data Quality Services
Dagster Labs
DataFlux Data Management (SAS)
DataObservability
DataOps.live
Datactics
GCP Logging
Great Expectations (GX) Core
IBM Data Quality
IBM InfoSphere Information Analyzer
IBM watsonx.data integration / Databand lineage in IBM ecosystem
Informatica Cloud Data Quality
Informatica Cloud Data Quality (CDQ) / IDMC
Informatica DQ
Informatica IDQ
Oracle Data Quality
Oracle EDQ
Ovalidge
Precisely Trillium / QualityStage
SAP Data Quality / SAP Information Steward
Snowsight
Trillium Software
Unravel Data
dbt-expectations
digna
Discontinued, still offered
No shut-down product was recommended here.